AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 305 · 40 questions

AI tip (Fair data, fairer AI): Bias usually comes from the training data: if a group is missing or shown in only one way, the model copies that. One-sided data: one age group, only ripe mangoes, only adult voices, only neat handwriting. Balanced data: many ages, colours, voices, regions and styles. Reduce bias: add varied examples, check who is missing, test on many groups, fix wrong labels and listen to complaints.

1. 1.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
2. 2.Which of these adds to bias? (a) add varied examples (b) ask different people (c) add more of the same (d) test on many groups
3. 3.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
4. 4.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
5. 5.Which of these helps reduce bias? (a) skip testing (b) test on many groups (c) test on one group only (d) ignore complaints
6. 6.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
7. 7.True or false: “add varied examples” helps reduce bias. (a) True (b) False
8. 8.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) more varied data (d) ignoring mistakes
9. 9.Which of these helps reduce bias? (a) test on one group only (b) fix wrong labels (c) copy old unfair choices (d) add more of the same
10. 10.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
11. 11.Which of these helps reduce bias? (a) copy old unfair choices (b) test on one group only (c) balance the data (d) skip testing
12. 12.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
13. 13.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
14. 14.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
15. 15.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
16. 16.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
17. 17.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
18. 18.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
19. 19.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
20. 20.True or false: “test on many groups” helps reduce bias. (a) False (b) True
21. 21.True or false: “add more of the same” helps reduce bias. (a) False (b) True
22. 22.Which of these helps reduce bias? (a) skip testing (b) check who is missing (c) use one group only (d) ignore complaints
23. 23.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) the weather (d) its screen size
24. 24.True or false: “skip testing” adds to bias. (a) False (b) True
25. 25.🔍 Which is the odd one out? (a) check who is missing (b) ask different people (c) use one group only (d) add varied examples
26. 26.Which of these adds to bias? (a) fix wrong labels (b) ask different people (c) use one group only (d) add varied examples
27. 27.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) fix wrong labels (d) copy old unfair choices
28. 28.True or false: “ignore complaints” adds to bias. (a) True (b) False
29. 29.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) test on one group only (d) ignore complaints
30. 30.True or false: “test on one group only” adds to bias. (a) True (b) False
31. 31.True or false: “test on one group only” helps reduce bias. (a) False (b) True
32. 32.🔍 Which is the odd one out? (a) ask different people (b) copy old unfair choices (c) ignore complaints (d) add more of the same
33. 33.🔍 Which is the odd one out? (a) fix wrong labels (b) check who is missing (c) add varied examples (d) add more of the same
34. 34.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
35. 35.🔍 Which is the odd one out? (a) skip testing (b) use one group only (c) check who is missing (d) test on one group only
36. 36.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) test on one group only (d) add varied examples
37. 37.Which of these helps reduce bias? (a) ignore complaints (b) ask different people (c) copy old unfair choices (d) test on one group only
38. 38.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
39. 39.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
40. 40.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False

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